Research On Key Technologies Of Streaming Media Cache For Mobile Edge Computing

With the increasing popularity of mobile streaming media services and networked mobile devices,the global mobile video traffic shows an exponential growth trend.The traditional cloud computing model can no longer meet the needs of 5G with low latency and high speed.With the emergence of mobile edge computing,computing and stor-age resources can be introduced at the edge of the mobile network(ie,base stations or terminals),thereby providing high-bandwidth and low-latency transmission capabilities,which can effectively reduce network load and improve network service quality.High-definition online video is a very typical application scenario in mobile edge computing.When playing real-time video on the network or transmitting locally cached video files,it is necessary to break the streaming media data files into packets for intermittent asyn-chronous transmission.However,due to the dynamic changes of the network,the data packets are not ”queued” and transmitted along the same path,and they will be out of order when they reach the client.The smooth playback of video and other streaming me-dia needs to rely on caching technology to exchange space for time.Through an efficient caching strategy,the impact of network congestion can be reduced or even eliminated,effectively solving the problems of video jitter,playback lag,and slow playback.In the face of the above problems and challenges,this paper mainly studies the streaming media caching strategy for mobile edge computing scenarios.It aims to reduce the content transmission delay and improve the cache hit rate,starting from the cache lo-cation,content preference model,cache update strategy,user mobility,etc.We designed and implemented a fine-grained hierarchical edge caching model(P-FHEC)based on con-tent popularity and a mobile video streaming edge caching strategy(ECMSP)based on user speed and video popularity.The former adopts a fine-grained and hierarchical edge cache architecture.By constructing a cache network model,the transmission cost,trans-mission delay,cache hit rate and user experience quality are modeled.It has designed the P-FHEC algorithm,which can cache more popular streaming media content in a limited cache space.The latter proposes the problem of maximizing the joint cache hit rate and minimizing cache delay by building a network model and a video cache model.It de-termines the area span of the base station edge buffer and the allocation of buffer space according to the user speed,and determines the priority of video buffering and update ac-cording to the video popularity.It designs and implements the ECMSP algorithm,which reduces the influence of the handing over between the base stations and service interrup-tion during user movement.In order to verify and evaluate the performance of the designed caching strategy,a mobile streaming media edge caching strategy simulation experiment platform was built.We have designed the data structures and functions of video files,mobile users and base stations,and modularly combine the user equipment model with the road traffic model that meets the characteristics of mobile users.Through experiments,the performance of the P-FHEC model and ECMSP model is compared with the existing cache strategies.The simulation experiment results show that the designed P-FHEC model and ECMSP model perform better in the mobile edge computing scenario,and can achieve lower average transmission delay and higher cache hit rate,which significantly improves users Quality of experience.